James Ransom
The Royal Society launched a policy briefing on research and innovation clusters today – I provided support for the analysis and wrote the case studies for Israel, Pittsburgh, and Uppsala.
The report is online here, and there’s a blog by Professor Richard Jones on Wonkhe introducing the report: can research clusters help level up the country? Research Professional also has coverage (paywalled article).
The 100 Resilient Cities programme resembled a large-scale urban experiment, with the strategies that many of the cities produced offering a rich source of information for analysis. Over 80 final strategies have been published; although cities from North America are overrepresented, there is broad geographic coverage.
As the previous iteration of the programme has ended, academic analyses of the strategies have continued to grow. For example, Taylor et al. (2020) use latent content analysis to assess how the resilience strategies of 14 cities in Europe, North America and Oceania conceptualise future uncertainty. Fitzgibbons and Mitchell (2019) examine the extent to which 31 resilience strategies focus on social equity and justice using content analysis; their sample included cities from the Global South and North.
I have compiled a spreadsheet of all the published strategies here (last updated July 2020). Please feel free to add any that I have missed. At the time of writing the 100 Resilient Cities website (home to most of the strategies) appears to be offline, so let me know if you would like access to the complete set of strategies, which I have both as PDFs and plain text files.
A new report published today explores how different sectors can work together to improve health outcomes at a regional level. I was delighted to be the lead author for this report with NHS Confederation, the Yorkshire & Humber Academic Health Science Network, and Yorkshire Universities.
Read the report 📖 (PDF), read the coverage in the Yorkshire Post 📰 or visit the campaign website 🌐.
Even before the pandemic, the government had given a clear commitment to ‘level up’ the regions, which means enabling regions to realise their full potential as part of an overall plan to narrow gaps in prosperity across the country. The economic aftershock of COVID-19 will hit communities hard – making the levelling up agenda more challenging but even more vital.
The report welcomes the growing focus nationally on both ‘health’ and ‘place’ – and sets out how we can align these with a bold ambition for improving quality of life and economic opportunities.
There is a particular focus on the tricky but vital mechanics of cross-sector collaboration, bringing together universities, local government, the health and care sector, business and communities. The traditional wisdom of carefully nurturing partnerships over time needs to be balanced by types of rapid response and new partnerships forged in the response to COVID-19. Read the full report here.
A version of this article also appears in ACEEU Spotlight magazine 📖
I enjoyed speaking on a lively panel yesterday about regional development and innovation as part of the UIIN conference, relocated successfully from Budapest to Zoom. Together with Matthew Guest from GuildHE we discussed how to better understand the local role of small and specialist providers.
The work builds on experimental alternatives to traditional economic impact studies. I first explored the idea of institutional heatmaps on a post here in 2018, and then expanded on this at a workshop in South Africa later that year. Over the past 12 months I have been working with GuildHE to ‘map’ the impact of some of their members. In yesterday’s presentation I set out why I think the traditional ‘big number’ approach to measuring economic impact is out of step with what places need from their universities. Below I go further and list why I feel these studies are, mostly, flawed endeavours. (I should add that these are my personal views, not those of GuildHE!).
You don’t have to look far to see economic impact studies. My former employer had a flagship biennial report with a steadily-increasing figure for the impact of UK universities – £21.5 billion to UK gross domestic product at last count – which it has used successfully for lobbying and campaigning. As long as this figure keeps increasing, everybody is happy. Many institutions have their own studies – £650 million of impact here, £400 million impact there – and often with LEP-level or regional disaggregation. Of course, such studies are not limited to higher education. We’re informed that shooting contributes £2 billion to the UK economy and supports the equivalent of 74,000 full-time jobs. Ornamental horticulture and landscaping contributed £24.2 billion to national GDP in 2017.
There are helpful academic papers which deconstruct the methodologies for calculating economic impact, and the common pitfalls. Instead, I want to challenge the preoccupation we seem to have with ‘one big number’ impact studies and what we lose in the process.
There are two shifts taking place which render the traditional impact study less effective:
I should note that economic impact studies are not all bad. It is helpful to see returns on investment, and to raise awareness that universities have economic clout and should be seen alongside other major industries. But they risk being a blunt instrument, obscuring what is often highly patchy and inconsistent local impact behind impressively large numbers. Economic impact studies need to be married to a rich understanding of local impact – perhaps through something like an institutional heat map combined with a survey of perceptions or social impact assessments.
Four further shortcomings that come to mind:
Above all, my concern is that economic impact analysis can mask inequalities and ‘cold spots’ in university engagement. Of course, heatmapping as an experimental alternative brings its own set of issues. Consistency between institutions, subjective judgements over the importance and intensity of shading, and the complexity of trying to map such a wide range of activity are issues that need to be resolved. But they may also expose quite starkly where a university is not working, and not having an impact – things that are hidden in the ‘one big number’ approach.
(Image credits: original images from Unsplash here and here.)
Yesterday Nesta published a report arguing that some parts of the UK have missed out on £4 billion of public research and development (R&D) funding each year, plus a further £8 billion of private sector investment. Some of these regions never fully recovered from the 2008 Great Recession, and COVID-19 threatens to deepen these divisions.
The Government’s target – set before the pandemic – called for the UK to increase investment in R&D to 2.4% of GDP by 2027, and by 3% in the future. The importance of this target is now greater than before. To meet it means empowering those regions with the lowest R&D intensity and recognising and supporting the vital role of universities and other partners in these regions.
Proposals in the report include devolving a substantial portion (25%) of the promised uplift in the R&D budget to nations, cities and regions, delivered through ‘Innovation Deals’.
The report also recognises how historic policy decisions have led to path dependency for regions, entrenching a set of ‘winners’ and ‘losers’. (This factor is missing in some – otherwise reasonable – recent reports which instead advocate building on existing centres of excellence). As the Nesta authors put it:
The current situation is the result of a combination of deliberate policy decisions and a natural dynamic in which these small preferences combined with initial advantages are reinforced with time.
Decisions made by previous generations of policymakers and politicians also play an outsized role in the UK’s industrial policy.
This excellent piece on efficiency and redundancy in the UK, and how we need more of the latter at the expense of the former to ensure resilience, is taken forwards nicely by Andy Westwood in this discussion of building industrial capacity in the UK. Building in redundant capacity is seen as a signature trait of a ‘resilient’ city or region. Andy sets out the case for starting with ‘national self sufficiency’ in health and manufacturing but then rapidly broadening out to other sectors, with a focus on impact at the local level. Movement towards autarky is a balancing act needing careful trade-offs, but there is a strong case for securing – or at least diversifying – supply chains in key industries and sectors.
The pandemic has drastically curtailed trade and investment; a return to previous patterns of international cooperation (which differ across UK regions) following COVID-19, and when trade picks up, is unlikely. More emphasis will be given to secure and resilient supply chains within the UK and near neighbours. This means strengthening industrial capacity and domestic manufacturing in the UK, and ensuring the provision of critical goods and services across the country – with clear implications for spatially-aware policymaking and an opportunity for rebuilding local economies.
These discussions neatly fit with a few themes I have touched on in recent posts – on how discussions over the smart city have morphed into ones about self-sufficient cities, on the risks of poor policymaking for resilience, and why popular narratives around ‘resilient communities’ are dangerous. See also this piece by Yorkshire Universities on The Coronavirus Pandemic: Universities and the Economic Recovery of Place.
This post originally appeared on the Yorkshire Universities website.
I’m a little late in reading Janesville: An American Story, Amy Goldstein’s tale of an industrial Wisconsin town in the depths of the Great Recession. The book received wide praise when published in 2017, telling the story of a community trying to pick itself up in the years following the closure of a major General Motors assembly plant. But the story has particular resonance now, as we stand on the cusp of another wave of economic upheaval. Here are three reflections.
Five years after the General Motors plant closed, the shock of vanished jobs has faded. But ‘the ways that time and economic misfortune can rend even a resilient community – a community determined not to lie down and give up – are plain to see’. Goldstein describes the emergence of two Janesvilles: one of business owners that emerged relatively unscathed, and another large group of struggling families. For this group, part of a ‘broad tumbling downhill’, the future is uncertain, incomes have halved, mortgages outstrip house values, food stamps have replaced eating out, and health insurance stops.
Inequality is at the heart of recent work by Yorkshire Universities on health and wealth, including a forthcoming report with NHS Confederation and the Yorkshire & Humber Academic Health Science Network (AHSN). Just before the pandemic struck, Sir Michael Marmot published a report showing widening regional disparities in life expectancy, including falling life expectancy for the poorest. In Yorkshire and the Humber, healthy life expectancy at birth is lower than the national average – with stark variations within the region too. Absence from work because of sickness is greater than the national average. Mortality rates are uniformly higher.
The danger is that the long-term economic impact of coronavirus exacerbates these inequalities. A briefing paper from the Institute for Fiscal Studies makes uncomfortable reading, referencing a study that showed a 1% fall in employment leads to a 2% increase in the prevalence of chronic illness:
To put this in context, if employment were to fall by the same amount as it fell in the 12 months after the 2008 crisis, around 900,000 more people of working age would be predicted to suffer from a chronic health condition. Only about half this effect will be immediate: the full effect will not be felt for two years. The shock to employment from the coronavirus pandemic is likely to be much larger than this and so we may expect a larger rise in poor health.
The poorest in society are hit hardest by recessions, driving wider inequalities in health and wealth, and splitting towns and cities into two.
‘It isn’t simple to take someone with a high school degree and a factory job and help lead them into new work’, reflects Bob Borremans. Bob is a community leader and head of Janesville’s job centre, and faces an uphill battle despite enthusiastic trainees and injections of federal cash.
Retraining and re-skilling are obvious responses to job losses and economic restructuring. But promised jobs at the end of retraining do not always materialise, and the path to graduation is tough. In Janesville, many former factory workers turned to courses at Blackhawk Technical College funded by federal grant programmes. Despite the laudable work of the college, the average pay of those who graduate is a shadow of their pre-recession wages.
The UK’s What Works Centre for Local Economic Growth concludes that employment training programmes for adults can have a positive, although modest, impact on earnings and employment. The key to success is designing appropriate programmes. A review of the evidence by the Centre found shorter programmes (below six months) are more effective for less formal training activity, and that longer programmes generate employment gains when the content is skill-intensive. On the job training programmes tend to outperform classroom-based ones. Further and higher education providers should bear this in mind in the months and years to come.
Janesville is proud of its ‘can-do spirit’, a trait that can be traced back generation to generation, to the industrious and hard-working communities that first attracted the likes of General Motors to the town. The problem is that a can-do spirit is, by itself, rarely enough to save a town struck by economic upheaval.
In another project, I have been exploring how world-leading research clusters have emerged in certain places – from advanced manufacturing in Pittsburgh, to life sciences in the Stockholm-Uppsala region, to the high-tech industry in Israel. Many of these have a popular ‘origin story’, often spun by an enthusiastic local press. The story usually goes something like this. The town has a proud past rooted in a particular industry. Economic calamity strikes due to wider structural forces. The proud industry is obliterated. There’s mass unemployment, and, temporarily, hope is lost. But the community is resilient and bounces back through sheer determination and hard work, attracting a new industry and forging a new, bright future – a high-tech phoenix rising from industrial ashes.
The reality is often messier, and the roots of any revival go back much further than the economic calamity. Take Pittsburgh. The steel industry in the city collapsed in the 1980s and the unemployment rate hit 18 percent. The city’s revitalisation is often explained by the grit and character of Pittsburghers, whereas the seeds of revival were planted decades before when the steel industry was at its height. Philanthropic investment led to specialist expertise being developed at the University of Pittsburgh and Carnegie Mellon University, including a new medical school, forming the foundation of Pittsburgh’s research and innovation clusters today.
There is a similar story in Sweden. When Pharmacia, then one of the largest pharmaceutical companies in Europe, merged with the US company Upjohn in 1995, around 200 research and managerial positions were moved out of Uppsala; the move was initially seen as striking a huge blow to the region. The popular narrative is that the vacuum left by the company’s withdrawal led to a frenzy of entrepreneurial start-ups and innovative ideas. But the emergence of the Uppsala cluster is the result of industrial and academic collaboration over at least 70 years.
The message here is not that people and communities are not important. Specialisation builds on rich legacies, and new clusters form around old industries. Some people – especially the highly-skilled – will thrive; employment in automation and industrial machinery in Pittsburgh is more than twice the national average. But people need to be empowered by structures and institutions that support them. Some places are fortunate to have seeds planted long ago, such as a strong university. Despite the challenges such institutions will be facing themselves, they will need to step up. For places those without, relying on grit will not be enough.
(Photo by Science in HD on Unsplash)
What follows is a simplified version of this workflow. It’s great for rapid literature surveys, and I’ve done a few recently for non-academic projects. No reference managers or specialist software are required. I use Ulysses for Mac to do my writing in the workflow below, but any text editor on any platform will do.
Save all the documents you will be reviewing in a folder. Optionally, split by type: in the example images below I have a folder for academic articles, and another for assorted reports, website pages and other publicity material.
Number these sequentially, as in the images. As you work through them, you may wish to label them as read (I’ve used a green tag to remember which ones I have reviewed).
(Skip to the bottom if you’re a Mac user and want to know how to find articles on Google Scholar incredibly quickly).
If it will save sorting time later, create headers in a text document corresponding to the final output. For example, in my latest project this was simply ‘introduction’, ‘development’, ‘outcomes’, ‘future’.
As you read each document, copy and paste the key information into your text file. The less you copy, the easier the final review becomes. Before each extract, put the document number or letter from step 1. Add comments if helpful.
Ulysses offers advantages for taking notes: you can quickly navigate between headers using keyboard shortcuts, and you can easily distinguish comments from pasted text. But other programs will work fine.
In this example, after working through 19 documents I had over 7,000 words of notes, which was a little unwieldy. To speed things up later, I had identified themes and quickly moved text around within new sub-categories (two or three within each of the four main headers). This should be a quick and crude exercise; don’t worry about missing things as the next stage will capture these.
Create a copy of your notes. Name it something like ‘DELETABLE’ so you don’t mix it up with your main notes.
You now begin writing. As you draw from your notes, cite the source with the number of the document, preceded by any unique character (in the image below, the footnote would contain the text “@3” to indicate source document number 3, for example, with the page number included if needed). The reason for the unique character will become clear in the next step.
When you’ve included content from your notes, delete it from the copy. If you decide you no longer want or need to use an extract, delete it. As you proceed, the copy of your notes will get shorter and shorter.
In Ulysses, I have a second editor open with the deletable notes on the left, and the final output being written on the right.
When you’ve finished writing, do a find and replace on each source reference (e.g. “@3”) with the full reference. Saving this until the end means you aren’t distracted with referencing when you should be writing. And using the unique character before the source number (e.g. “@”) means you aren’t searching through every number in the document.
As with the previous longer workflow, the flow in workflow is important. For effective results, do all of the above quickly. Any wait between collecting extracts from documents and writing means the broader context (information that you haven’t copied and pasted, but will be in your mind), is likely to fade.
I use the excellent Alfred application for quick keyboard control of my computer. A custom search allows me to search Google Scholar from Alfred, by typing ‘scholar’ followed by the search term.
Here is how custom searches work, and here is my custom search (if you have Alfred installed, clicking this should import to your library).
This post originally appeared on the Yorkshire Universities website.
Unsurprisingly, a huge amount is being written about the coronavirus crisis. Publications are shifting their entire focus onto the pandemic (‘there is only one story in the world right now’, says WIRED magazine). There has been an explosion of academic publications on the virus, with peer review processes struggling to keep up.
In parallel, we’ve been looking through previous writing to find clues on how to deal with the crisis, and whether the warning signs were there. In 2015, Bill Gates explained how we are not ready for a future epidemic. In 2007, scientists in Hong Kong wrote a scarily prescient paper on coronaviruses, describing with great accuracy the ‘time bomb’ that went off in late 2019 in Wuhan, China.
One idea I’m revisiting is resilience. There are two sides to the concept. The first is empowering: a resilient place returns to normal as quickly as possible after a shock or a disturbance. Such places are flexible and adaptable, learn from previous crises, prioritise skills training, have inclusive societies, encourage innovation, develop diverse industries, and promote clear and transparent leadership. Although the terminology differs, policies around devolution and decentralisation to cities and regions have many of the same aims.
The other side is less rosy. As the concept gained traction in the early 2010s, cities in particular came under pressure to demonstrate their resilience. Leaders shouldered growing responsibilities for their city to tick the latest urban and regional policy boxes – to be sustainable, smart and resilient. However, as Lawrence Vale has written, ‘uneven resilience threatens the ability of cities as a whole to function economically, socially and politically’. Boosting resilience at a local level requires substantial resources and reliable support over long periods of time. Programmes to encourage resilience around the world have proven to be less than resilient themselves.
Shifting the power to tackle local issues and to respond to wider challenges from nations to regions is welcome. But if only responsibility is transferred, without accompanying resources where local institutional capacity and capability is limited, it is unlikely resilience – or devolution – will be successful. As we gradually turn to the economic recovery in the coming months, as government policies to ‘level up’ the regions return to the agenda, and as we consider how to prepare for future crises, it is worth revisiting the literature on resilience.
Photo by Alex Kim on Unsplash
There’s plenty being written at the moment about staying sane whilst working from home, adapting to the change of lifestyle, and maintaining effective communication with distant colleagues. But here are four tools that have helped me to actually get good work done whilst I work from home (which I did two or three days per week until October 2018, and have done full-time since). Most of these are equally applicable in an office, but can seriously improve your output at home.
Carefully chosen music can encourage deep focus and boost productivity. The best tool I’ve found for this is Brain.fm. The service boasts of ‘Functional Music to Improve Focus in 15 Minutes’. Regardless of whether the science behind the music stacks up, I find it invaluable for tasks requiring concentration (most of my PhD so far has been written to the ‘Cinematic Music Focus’ station). This link provides a free trial.
A free alternative (but be wary of adverts interrupting your flow) is computer game soundtracks on YouTube – or playlists of such music on Spotify or other music services. These are designed to engage you in the task at hand and for background distractions to fade away. This YouTube channel is a good place to start.
A very basic recommendation, but an essential one. I use an AmazonBasics laptop stand that cost a little over £10. It will save your back and neck. Requires separate keyboard and mouse, which are also worthwhile investments.
Stop yourself from mindlessly browsing the news or social media with a distraction blocker. I use Freedom which can block websites and applications – useful to shut off email for set periods of time or on a schedule. The very act of turning it on helps me to get into work mode, and once running it enables me to work more deeply on tasks for longer. There are several open source alternatives that I’ve used in the past, but Freedom offers more control and customisation.
Depending on the task, the pomodoro technique provides great results. You’ll need to experiment, but I find tedious tasks or reading articles and reports are perfect. Seriously applying the pomodoro technique also allows you to track and increase your focused work time.
I use an open source application called Tomighty. There are more advanced options for Mac discussed here.
Working from home offers an opportunity to experiment with new routines, workflows, habits, tools and ways of working. Through experimentation I’ve developed ways of writing, researching and managing flows of information that have worked well for me and I will post more about in the coming weeks.
I am currently supporting a higher education project in Tunisia and came across an interesting World Bank study considered to be the first of its kind. Final year undergraduates were given the opportunity to graduate with a business plan instead of following the standard curriculum, and were offered 120 hours of training that included ‘most of the components that are considered best-practice for entrepreneurship education’. The optional entrepreneurship track started in 2009/10 and has been running since.
In the first published analysis, short-term impacts were studied:
the entrepreneurship track was effective in increasing self-employment among applicants, but that the effects are small in absolute terms. In addition, the employment rate among participants remains unchanged, pointing to a partial substitution from wage employment to self-employment. The evidence shows that the program fostered business skills, expanded networks, and affected a range of behavioural skills. Participation in the entrepreneurship track also heightened graduates’ optimism toward the future shortly after the Tunisian revolution.
A second paper, published in 2019, examined the medium-term impact using the same cohort:
The medium-term results show that the impacts of entrepreneurship education were short-lived. There are no sustained impacts on self-employment or employment outcomes four years after graduation. There are no lasting effects on latent entrepreneurship either, and the short-term increase in optimism also receded… the lack of medium-term impact holds across sub-groups based on gender, family wealth, skills or social capital.
There are several possible lessons to draw, beyond the clear difficulty of achieving lasting impact. The first is that integrating enterprise education alongside existing curricula, rather than a separate stream, could be an effective alternative. The second, as the second study suggests, is that other limitations are a bigger constraint than the nature of the training, especially accessing capital (there is evidence from Nigeria, cited in the paper, of monetary grants having long-term, positive impact). The third is the importance of continued coaching, training and mentoring beyond the initial period of study.
But what really struck me was how relatively unusual it is to come across randomised control trials of interventions in higher education (and especially published studies of those where the intervention did not work). Fields such as medicine abound with multi-year trials. Primary education has also seen its fair share – this years Nobel prize recognised the work of Abhijit Banerjee, Esther Duflo and Michael Kremer popularised in the excellent book, Poor Economics. There are plenty of large-scale evaluations and analyses of higher education, particularly around student outcomes, but I struggle to think of large-scale, experimental interventions. My hunch is that, as recognition of the role of higher education in development and social change has increased, so too will demand for randomised control trials within the field.
The Tunisian study is helpful as it shows that a ‘common sense’ prescription (give students business and entrepreneurial skills instead of writing an academic thesis as part of their degree) to a commonly-perceived problem (unemployable graduates) simply did not work. I’d love to see more such studies. Sharing examples of what doesn’t work through large-scale, rigorous testing can be hugely valuable, albeit with the caveat that the results may not always be generalisable to other contexts. As I see it, several things need to be in place:
Crucially, these conditions combined distinguish a rigorous, experimental study from a public policy intervention. If you know of any other experimental, evidence-based studies in higher education – especially those that have been deemed to have not worked – please let me know by email or in the comments below.
Photos of Tunis, Tunisia from Unsplash. Credits: main image, article image.
